@@ -29,13 +29,8 @@ Grain boundaries (GBs) are crystalline borders between single crystals in materi
role in mechanical, chemical or electronic response of materials and are therefore an essential focus of materials science
and physics.
To simulate grain boundary properties using atomistic codes such as ``LAMMPS``[@LAMMPS],
the atomic structure of the GBs need to be generated first. GBs are geometrical entities with a large parameter space
that has been well formulated within a coincident site lattice (CSL) mathematical framework. ``GB_code`` uses the CSL
construction to generate GB atomic structures (currently for cubic materials) systematically and provides input atomic
structures for atomistic calculations (e.g. ``LAMMPS``[@LAMMPS]). These atomistic codes can further calculate different
properties of the GBs. In addition to providing the input structures, the ``csl_generator.py`` script and the attached
Jupyter notebooks have extra functionality to show how the CSL properties can be used to locate, classify and categorize
GBs are geometrical entities with a large parameter space that has been well formulated within a coincident site lattice (CSL) mathematical framework. ``GB_code`` uses the CSL construction to generate GB atomic structures (currently for cubic materials) systematically and provides input atomic structures for atomistic calculations (e.g. ``LAMMPS``[@LAMMPS]). These atomistic codes can further calculate different properties of the GBs. In addition to providing the input structures, the ``csl_generator.py`` script and
the attached Jupyter notebooks have extra functionality to show how the CSL properties can be used to locate, classify and categorize
different GBs and to extract detailed information about them; which causes it to be a good interactive toolbox to learn
about grain boundaries and versatile for running high-throughput calculations.
